Worlds Colliding: Navigating Converging Forces

Bryant VanCronkhite: Hi, I'm Bryant VanCronkhite, co-head of the Allspring Special Global Equity team, and welcome to SpringTalk. In this episode, I'm going to sit down with Mike Smith, the head of the Growth Equity team at Allspring. And we're going to discuss a few topics that we think are critical to understanding and appreciating in today's market environment. We're going to talk about what it means to own a quality company. How should we define the word quality? We're going to talk about whether the benchmarks are active or passive and what they really do for active managers. We're going to discuss AI and how all these dynamics are colliding in an episode we're calling Worlds Colliding. Understanding how these dynamics work together and how they impact the markets and active portfolio management is critical in our minds. And this conversation brings it together in what we hope is a very fun and educational way.

Mike Smith: Worlds colliding. Collide is a violent word. Bryant chose that word on purpose when he came up with the title, and I love it. I think it's often the case in investment cycles where there's a zeitgeist issue. AI is defining the cycle that we're going through right now, but it's also true in various cycles. There are other things going on that don't get the same attention or the same recognition, but the fact that those things are present and bumping into each other and bumping into AI right now is actually critically important. So, we hope to connect some of these dots as well as we go through the conversation. And I'm going to kick it to Bryant for his favorite topic, which is quality.

Bryant: Quality is one of my favorite topics because it's my least favorite word. It is perhaps one of the most dangerous words in the investing dictionary, because almost everyone says they're a quality manager. It's overused and poorly defined. And I'll go one level further and say that it's always evolving. And I think most investors think of quality as a set of characteristics and output, if you will. But maybe we need to evolve a little bit and think of it as an outcome pattern, or maybe it's defined by a qualitative factor on an asset base. But at the end of the day, in my mind, what we need to think about right now is that the conditions are changing and therefore it's highly likely how we define quality has to change.

Mike: I think you hit on the most important aspect of quality in my process and yours, which is just the permanence or the duration. It's one thing to be great once. It's another thing to be great for a long time. And I think quality changes over time. And you hit that really well. I want to come back to just the word itself and the definition for a second, because I think that's important as well. And I think it's unfortunate when you look at any kind of a borrow report or a factor model on a portfolio, you'll see a whole menu of factors, and some of them are things that you don't come across in your daily life, like residual volatility and long-term reversal. But some of the factors are named with words that we come across regularly, like quality. And I think that's actually unfortunate because I think for most people the word quality tends to mean safe or reliable. That's not what quality means in investing. There's nothing safe about a quality stock, especially if those qualities start to change. And I think that's where the collision has happened. When you look at this slide in the lower right, if you were overweight quality in 2025, depending on how overweight you were, you had a really bad year. There was nothing safe about that. And the big reason for that is because people were recalibrating what quality businesses are and how long those characteristics can last, just like Bryant laid out. So, I would just suggest in our work lives and especially in front of clients, let's be really, really careful with how we use the “Q” word. Let's remember, factors are an output of a portfolio defined by their fundamentals, not meant to be an input. And let's help educate our clients that— in investing, at least—quality does not mean safe.

Bryant: And, Mike, maybe I'll add to that one more thing. I think people like to ask, so what? How does this impact what you're doing? And what it doesn’t mean for our team—and I don't want to speak for Mike or other teams—is that you have to change what you believe creates value, right? The foundations and principles for how you think companies create value don’t have to change just because the conditions in which you're executing are changing. But maybe we need to open our aperture a little bit and allow the funnel to be a little bit wider, or maybe avoid the words “we don't do that” or “we don't invest in those areas” because those areas might be the new definition of quality. And so, it's not about changing who you are as investors. It's making sure you give yourself the freedom to apply your process to a wider set of potential outcomes given a new set of conditions.

Mike: So, with that in mind, switching gears to topic two: benchmarks. What are they good for? Are they really neutral? I think there's a buried lead when it comes to indices. And it's particularly important in our small- and mid-cap businesses because the way Russell creates their benchmarks, their methodology has stayed constant while the world around them has changed significantly. And what I mean by that, when you look at the slide on the upper left, when my investment career began, there were over 8,000 stocks that traded, 8,000 companies that you could call and ask questions, and 8,000 tickers that you could look at every day on your screen. That universe has been shrunk in half. The Russell 3000 is the top 3,000 stocks in the market. So where am I going with this? Why is that important? Well, they have not changed their methodology. It's still the Russell 3000. It's not the Russell 1500. And the way they build their indices it's like a layer cake. So, they take the 3,000 largest stocks in the market. That's their universe. They push everything else to the side. So, what got pushed to the side in 1997 was about 5,000 companies that were too small, too illiquid, not profitable enough, sort of too junky to be in an index of any kind. And then from there they built their 1000 index, which is the large-cap index. The 2000 is the small-cap index. And then the SMID and mid-cap indices are a Venn diagram of those two universes. Well, if you fast forward to today because they haven't changed their methodology, those 5,000 companies that were not the best companies to look at that didn't used to be part of the scope are now in the index. That is the reason why close to one-third of the Russell 2000 is composed of companies that don't make money and probably never will. So, put that in the context of we just told you—quality changes over time, and it's meant to be an output, not an input. That is true. It's also true that if you're saving for retirement or trying to achieve a long-term goal in your equity portfolio, and you're buying an index that's comprised of $3 out of every $10 in companies that don't make money and probably never will, I think you have to question what you're trying to achieve and how you're going to get there. And I think as we go about our day to day and we use various benchmarks to compare ourselves, number one, if the client wouldn't buy the benchmark, is that the best comparison, or are there secondary measures or other things to look at? Number two, if there's that much exposure to businesses that don't make money in the index, is it as neutral as it used to be, or is it more volatile than it used to be? And I think that's a hidden change in the market that most people don't fully appreciate. But increasingly I think it's a very important issue.

Bryant: Yeah, I think it's a huge issue. And neither of us are here to bash the benchmarks. We have to have benchmarks. Our clients think about us as managing to a benchmark. We need to ground zero because what we do every day is allocate risk. And the benchmark defines the level of risk, the type of risk we're taking. So, we need those. But what I find interesting is that number one, people invest for three reasons, as I see it. They invest to grow their wealth, they invest to preserve their wealth, or they invest to get income off of that wealth. I think it's interesting that our industry has chosen to say that, well, the best way to think about those three goals is to start with how big a company is and the valuation of that company. Those are the two frameworks in which we think about creating boxes and asset allocation models. I think one of the big unlocks for our industry is to say, is that right? Or are there better ways to define the DNA of which a framework or outcome should be defined? And, so, when it comes to the benchmarks, what I think is critical to know is that these are changing rapidly. Just because the small-cap value universe or the large-cap growth universe exhibited certain characteristics last quarter, last year, five years ago, and as a result, created outcome patterns that looked like x, y, and z outcome, that has no bearing on whether it will do the same thing next quarter or next year. The underlying names are changing, and I would say more recently changing more rapidly and more significantly. But number two, so is the DNA, right? We talked earlier about factors as being maybe a measure of quality or an outcome of quality. These factors as I look at it are the DNA of the underlying securities within each of the style boxes. All right, let’s move to the next topic. And this is one I like. This is one I love because talk about worlds changing and understanding how they impact what's happening. So, if you go back 25 years—and Mike and I have looked at a bunch of different third-party sources for this—20-plus years ago, the volume of securities that was traded every day was 80% tied to people like Mike and I and most of our peers and partners in this firm, the fundamentally driven, long only or hedge fund crowd that has a view on the fundamental value of business based on their analysis of the company, its cash flows, etc. 20% of trading volume 25 years ago was tied to what we now call retail. Maybe you can lump in thematic, you can lump in factors. That was the ratio. And that meant that the average price was set day to day by people who have that fundamental view. Today, that is completely flipped. Today, 80% of the volume traded on any given day is by someone who, by definition, does not have a view of the fundamental value of the business. They're thinking about it as a theme. Think of all the market dynamics right now around. I want to invest in the space theme, AI, capex, memory theme. I want to go high quality, low quality. I want to go momentum or no momentum. It’s factor based. It’s thematic based. It's meme based. It's retail based. Their view of the world is very legitimate. The reason why they're trading and investing the way they are is legitimate, but it's very different from how Mike and I and our peers think. And as a result, that's what's setting the market price. Now, that has some ramifications that we need to either hope reverses if you don't like it or learn to play with. And, so, in my mind, through what we see, which I think is on the next slide, what you'll see is that the volatility of factors has increased meaningfully in a post-COVID world. The ramifications of people of the majority of traders every day thinking this way are creating a lot more volatility. It's creating a lot more bigger moves up and bigger moves down. And today we're seeing it. Today the SOX Index (PHLX Semiconductor Sector Index) is down. Last I looked it was down over 5% because people are saying I need to get out of AI. They're not saying I have a view on that company, or I have a fundamental analysis of the cash flows. I need to get out of AI and you get out of semis, right? And that's what's happening today. And, so, I think this is here to stay. What people are doing and the participation by that former 20% and now 80% is incredibly irrational. And their behavior and their actions are here to stay. I think the way they do it will evolve over time, and there'll be a lot of lessons learned and a lot of pain. But the volatility, the thematic, the factor is here to stay. As an active manager, you need to decide if you're going to just hope that it changes. Or are you going to learn to bring new tools to the battlefield of investing? Given that the landscape and what you're fighting every day has evolved in a material way?

Mike: I think Bryant's right. The way it manifests could change over time. And that means what we're seeing in the stock market could be cyclical. But there's a deep-rooted issue there that I think we need to include in our base case when we build our portfolios, when we save for our retirement, when we talk to our clients about what the long-term trends are. It's not the most pleasant thing to talk about, but I think it's a real issue and a hard one to solve.

Bryant: And just to bring it back to, so what? Like, what do we need to do about this? Well, I think one of the things we need to think about is how does this manifest itself in terms of the market dynamics and measuring risk. So, if the market's going to trade around themes, what does it mean for your desire to be offsides to that theme for one week, one month, one quarter? So, do portfolio managers need to tighten up industry weights and sector weights, or do you need to tighten up your beta, your momentum, as well? Again, to Mike’s earlier point, those are all outputs of an underlying process. But ignoring those risk factors might mean that you find yourself offsides for a period of time in a way that could be more painful than it would have been historically. It’s a fascinating dynamic right now. But what does it mean? It means that the gap between a fundamental manager's view of the long-term value of a company and the current price might stay wider than normal and stay wider for longer than normal. And how are we going to deal with that as active managers?

Mike: It's contributing to the volatility in the market. And I think you're spot on. It's a call to be more diversified in terms of how we build portfolios. OK, AI. We saved the best for last. So, here's the dessert. And I think most people probably have seen a slide like this before, but it's worth taking a minute to walk through. First of all, you can see down at the bottom. Those are the ticker symbols for the five largest hyperscalers, the companies that are spending the most amount of money to build out AI infrastructure. Second, you can see the change. $154 billion, which is a fact. That's an actual number from 2023, scaling to something over $1 trillion in 2027. And that is an estimate. And it's an estimate that keeps moving up at a pretty healthy clip. If you ask some of the folks on my team their forecasts, I think some people think that could be like $1.5 trillion by the time we get to the end of 2027. So, if you just play with that number, that's a 10x in 4 years. That doesn't happen very often, particularly when you're talking about big dollars. $154 billion is cute. That's actually a lot of money. But $1.5 trillion? Now you're talking about multiple percentage points of GDP. So, what's the point around that? I think it's not to call the top. It's not to stand here today and say AI is a bubble or it's not a bubble. I think it's too soon to answer those questions. We will only know in hindsight. I think the best we can do is try to have the most accurate forecast of where is that $1.1, $1.2, $1.5, $ 1.8 trillion number going? What are the funding sources—which is increasingly an issue—to pay for that investment? But really the most important question, which connects back to quality and the definition that Bryant and I use, is what's the return on that investment going to be? That's what every active manager should be trying to figure out right now, in my opinion. It's a fun time to be doing the work because nobody knows. There's no such thing as future facts, but there's a lot at stake if you can get that right. And I'm an optimist. I'm a growth investor. I don't short stocks, so I bring a bias a little bit to that conversation. But I have not run into a reason yet to not be bullish. The adoption of AI is very, very strong, unlike anything we've seen before. The potential it has to have an incredible impact on the way work gets done all around the world is still on the table. Nothing has punctured that dream. We just have to be really sharp in our analysis of, OK, how is the end user using this technology? What benefit do they get from it? How much are they willing to pay for that? Who's collecting that revenue? And just follow the money. And that's the work we all need to do right now. And then we also need to be open to the possibility of what happens next. That's always the most important question in investing. AI is no different. What new businesses will be formed that weren't possible before AI? What existing businesses that aren't really directly in the picks and shovels business or immediately thought of as an AI company are all of a sudden going to grow faster and make more money and be a better business because of AI?

Bryant: I want to approach it in what I think might be a bit of a different way. So, I think humility is perhaps the most valuable character trait you can have in the investing profession. It's OK to say I don't know. In fact, it might be the best thing you can do in most cases when you start doing research. That forces you to kind of put it aside and go where you have more confidence. When it comes to a few things with AI, I'm really confident. I'm super confident that there will be a lot more money spent over the next 5, 10, and 20 years in AI than hasn’t been spent already. I'm also super confident that not every one of those dollars will be spent well, which means we're going to have a wide range of ROICs (returns on investment capital) when it comes to a dollar spent in the AI arms race. I'm also super confident that today's winners aren't necessarily tomorrow's winners or the next year's winners when it comes to AI, so a lot of ground yet to be covered. This game, if you will, of trying to figure out AI is nowhere near being done to what Mike was saying earlier. And so, when I think about what's happening in the world today, I want to tie it back to where we started. What's quality? And Mike talked about the money being spent at capex by the hyperscalers. And this slide takes a look at the free cash flow historically and the projections for the hyperscalers as they ramp their capex up. Now, quality were the hyperscalers. These guys were deemed to be the quality businesses within the tech world for a very long time. Why? Because they’re dominant asset bases. They have huge network effects, huge market share positions. Those created strong and growing margins because they were low capital intensity. Remember, that's what defined quality—low capex, low capital intensity, low real assets. They had massive free cash flow margins and just threw off a ton of money that allowed them to go buy anyone that was going to compete with them, provide dividends, do buybacks, etc. That was quality. Everyone loved them. Then they started spending money. And, at first, everyone was like, oh my God, they're spending so much money. It’s going to be great for them. They're going to exaggerate their already big positions. They’re going to be the winners of the AI race. Then the market said, wait a second. Maybe that's not quality. Maybe all that capex is exactly what we should be avoiding. And by the way, they're going free cash flow negative in some cases. I'm going to sell those stocks off. And we saw that—a period where the hyperscalers and the big capex mega cap winners of the yesteryear became the losers. Then all of a sudden, people said, wait a second, but if they’re spending money and they're getting good returns, they are the best-quality companies. They are the winners. And, so, the market is trying to debate just these 5 or 6 companies—quality, high quality, low quality, high quality. It's evolving. Winner, loser. It's constantly evolving. And I think what we have today is finally the opportunity to do the work. Now starting back in 2025, Q2, Q3, Q4 even, it was hope. It was guessing. It was expectations because there were no real returns yet when it came to AI at this mass scale. We were trying to guess at who's going to win, who's going to lose, how you define quality, but now we're a year-plus in. There are actually returns you can measure based on these investments across these businesses. You can look at their access to capital, their funding sources, and their funding costs and the evolution there. And we see hyperscalers being winners. Someone else might not, but they're the winners of today in our mind or the winners of the future. And that will evolve to the next generation, the next generation, etc. So, my point being that this story is not fully written yet. We as investors finally have a chance to stop hoping, guessing, trying to chase the market, but do the work, figure it out, and build your portfolios accordingly. So, I'm actually super excited. Kind of like Mike is around AI about the opportunity, not just for AI from a business standpoint, from a social standpoint, but from an investment standpoint, the ability to get into the business of fundamental research and doing that work to figure out which companies are going to win and how to build our portfolios around it. So, we’re super excited about AI. Lots to discuss there, but that's my take on it in the current environment.

Mike: Should we wrap it up, Bryant?

Bryant: Yeah, we can wrap it up and I can give it a shot and then feel free to add on. But, look, thanks for listening to this and seeing through it. Hopefully it gives you some perspective on where Mike and I are just thinking you have to have an opinion. These are things that we have a lot of questions on. We have some perspectives. We might have a little bit of the answers, but we still are working through a lot of these issues. We think they're important to everyone who is participating in the investment landscape in any way, whether you're an asset owner, asset manager, or consultant in the middle, these questions are critical to how you go about defining what you do and how you do it in the future. And they’re colliding. Going back to Mike's introduction, any one of these individually could define a market generation or a market era, but they're colliding with force right now. And understanding that this is going to kind of constantly move around like water in a bathtub is going to help you understand where you need to focus, where you spend your time, and how to build your portfolios. I know for our team, it's having real significant impacts on how we approach our daily tasks, how we build portfolios, and how we're communicating.

Bryant (conclusion): Well, there you have it—worlds colliding in many ways. Thank you, Mike, for being a great partner at Allspring and for joining me for this conversation. And thanks to all of you for joining us. I hope you enjoyed it. Hope you can find value in a lot of it. And we'll see you on the next SpringTalk.